openstarlab preprocessing package
Project description
OpenSTARLab PreProcessing package
Introduction
The OpenSTARLab PreProcessing package is a core component for the OpenSTARLab suite, providing essential data preprocessing functions. It is designed with minimal dependencies and aims to avoid those that are heavily version-dependent.
This package is continuously evolving to support future OpenSTARLab projects. If you have any suggestions or encounter any bugs, please feel free to open an issue.
Installation
- To install this package via PyPI
pip install openstarlab-preprocessing
- To install manually
git clone git@github.com:open-starlab/PreProcessing.git
cd ./PreProcessing
pip install -e .
Current Features
Sports
Event Data
SAR (State-Action-Reward) Data
Space Data
RoadMap
- Release the package
- Incorporate more functions
Developer
 Calvin Yeung 💻 |
 Kenjiro Ide 💻 |
 Zheng Chen 💻 |
 Keisuke Fujii 🧑💻 |
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file openstarlab_preprocessing-0.1.37.tar.gz.
File metadata
- Download URL: openstarlab_preprocessing-0.1.37.tar.gz
- Upload date:
- Size: 138.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.8.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7d30bddabeb4f9dfbfb7a7348ee031efb0775796c988048b8059662a9973e2ae
|
|
| MD5 |
b4add875348f3ffe5eaa2ed43ea83811
|
|
| BLAKE2b-256 |
eb9824ebdc665e61a90fd9697dd1b3fb3f35ccbfb714b547e972bbe2765f9069
|
File details
Details for the file openstarlab_preprocessing-0.1.37-py3-none-any.whl.
File metadata
- Download URL: openstarlab_preprocessing-0.1.37-py3-none-any.whl
- Upload date:
- Size: 167.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.8.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
eb12c25ebf3284b8ac79180104f86e0a6d0a3067b4cb382d861a1b1cb463ff08
|
|
| MD5 |
10691d28e346a852596095c1a10f472e
|
|
| BLAKE2b-256 |
07a717f51d265cda9cd4f729c606f45f01cd4e5898bd11c135506309130590f3
|
